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dbt Labs dbt-Analytics-Engineering Exam Syllabus Topics:

dbt Labs dbt Analytics Engineering Certification Sample Questions:

1. You assume two columns of type 'numeric' will always align in terms of precision and scale (number of decimal places). What's a key way to design your models and tests to be resilient even if this assumption changes?

A) Avoid relying on exact equality when comparing values from these columns.
B) Always store all numeric values as strings to prevent these issues.
C) Use explicit casting functions to enforce matching precision during calculations.
D) Write tests to compare the column metadata rather than their contents.

2. You need to parameterize a dbt model that filters data based on a country code. Which approach offers the BEST combination of flexibility and security?

A) Build a dynamic query string entirely within a Jinja macro.
B) Use environment variables in conjunction with Jinja to substitute the country code.
C) Pass the country code as a CLI argument when executing dbt run.
D) Create a seed file mapping country codes to filter values and reference it in the model.

3. You need to run a custom Python script after your dbt models execute. Where and how can you configure this in your dbt_project.yml file?

A) Utilize the on-run-end hook configuration.
B) Create an 'integration test' and use the PythonFunction class-
C) Define it as a 'snapshot' to ensure it runs after all models.
D) Include the script as a 'seed' file with a specific execution order

4. After configuring a dbt package, you notice its models depend on a source table absent from your warehouse. How do you typically address this?

A) Override the package model's SQL query to reference an existing table in your warehouse.
B) Rewrite the package's model from scratch within your project to remove the dependency.
C) File an issue or submit a pull request to the package's repository.
D) Update your source definitions to include the required table.

5. You suspect discrepancies due to potential changes in upstream source tables. What's a practical first step to investigate?

A) Compare the current state of the source tables against their historical snapshots.
B) Run all dbt models and examine the logs for unusual entries.
C) Contact the team responsible for managing the sources to inquire about recent updates.
D) Review the dbt project's manifest.json for related changes.

Solutions: